Content management (CM) is the process for collection, delivery, retrieval, governance, and overall management of information in any format. The term applies to the administration of digital content, whether that content consists of images, video, audio, text, or multimedia.
When I think of content management, I think about marketing departments managing their messaging on corporate websites, or HR departments posting relevant articles and information on an internal corporate intranet. The natural inclination is not to think about content management in the world of big data algorithms and statistical analysis.
An emerging school of thought suggests we should change this thinking.
“A great example is large scale agriculture,” said Anthony Calamito, Chief Geospatial Officer at Boundless, a provider of geospatial technology solutions. “Many of these companies store vast amounts of data and imagery, but they haven’t thought through how to effectively store, index and manage the data.”
In part, the issue is technical storage—but an equally important concern is how to retrieve and display the most relevant data to a user.
In the data science world, this issue is addressed by iteratively perfecting algorithms that probe the data to find answers to important questions. But a companion need is to return information of high relevance that builds on these answers and gives users a more complete picture of not only the immediate questions and answers but of surrounding data content that explains the answers so that users have a complete understanding of the information that they can use for business decision making.
Reprint from: TechRepublic
See original at: https://openg.is/2R5ZKPL